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articles/cognitive-services/text-analytics/includes/quickstarts/nodejs-sdk.md

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[v3 Reference documentation](https://aka.ms/azsdk-js-textanalytics-ref-docs) | [v3 Library source code](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/textanalytics/ai-text-analytics) | [v3 Package (NPM)](https://www.npmjs.com/package/@azure/ai-text-analytics) | [v3 Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/textanalytics/ai-text-analytics/samples)
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#### [Version 2](#tab/version-2)
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#### [Version 2.1](#tab/version-2)
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[v2 Reference documentation](https://docs.microsoft.com/javascript/api/@azure/cognitiveservices-textanalytics) | [v2 Library source code](https://github.com/Azure/azure-sdk-for-node/tree/master/lib/services/cognitiveServicesTextAnalytics) | [v2 Package (NPM)](https://www.npmjs.com/package/@azure/cognitiveservices-textanalytics) | [v2 Samples](https://github.com/Azure-Samples/cognitive-services-node-sdk-samples/)
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articles/cognitive-services/text-analytics/quickstarts/text-analytics-sdk.md

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::: zone pivot="programming-language-java"
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> [!IMPORTANT]
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> * This quickstart is only for version `3.0-preview` of the Text Analytics client library, which includes a public preview for improved [Sentiment Analysis](../../how-tos/text-analytics-how-to-sentiment-analysis.md#sentiment-analysis-versions-and-features) and [Named Entity Recognition (NER)](../../how-tos/text-analytics-how-to-entity-linking.md#named-entity-recognition-versions-and-features).
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> * This quickstart is only for version `3.0-preview` of the Text Analytics client library, which includes a public preview for improved [Sentiment Analysis](../how-tos/text-analytics-how-to-sentiment-analysis.md#sentiment-analysis-versions-and-features) and [Named Entity Recognition (NER)](../how-tos/text-analytics-how-to-entity-linking.md#named-entity-recognition-versions-and-features).
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> * Be sure to only follow the instructions for the version you are using.
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> * The code in this article uses synchronous methods and un-secured credentials storage for simplicity reasons. For production scenarios, we recommend using the batched asynchronous methods for performance and scalability. See the reference documentation below.
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